ITECH7406 Federation Business Analytics and Data Mining Techniques Report

User Generated

fnvxhznepubxxnyn

Business Finance

ITECH7406

Federation University Australia

Description

Business analytics and Data Mining techniques can help organizations make sense of -- and gain a competitive advantage from -- all the data that they have in their systems. Business analytics includes “decision management, content analytics, planning and forecasting, discovery and exploration, business intelligence, predictive analytics, data and content management, stream computing, data warehousing, information integration and governance” (IBM, 2013, p. 4).

There are different types of business intelligence analytics that an organization can take advantage of, including predictive analytics, text analytics and text mining, sentiment analysis, customer analytics and business intelligence data mining. Data Mining is the process of analyzing large data-sets to identify trends and patterns in the data. The data can be generated through different sources such as social media, websites, transactions, mobile devices, sensors, etc. The information extracted from this data helps organizations to derive their real business value and generate new business opportunities.

In the light of above information write a 3000 words research report on specific business analytics and Data Mining techniques applications that derive business value and generate new business opportunities in any of the following three (3) industry verticals

Unformatted Attachment Preview

ITECH7406- Business Intelligence and Data Warehousing Research Report Group Assignment Sem1-2019 Overview For this assignment, the students will work in team and create a written report that will review the applications of business intelligence analytics and Data Mining in different industry domains in decision making contexts. The purpose of this assessment is to enable students to understand how business intelligence analytics and Data Mining techniques revolutionize businesses today. Timelines and Expectations Percentage Value of Team Report: 15% Percentage Value of Team Presentation: 10% Group Presentation Due Date - Week 08 –Timetabled Tutorial Group Report Due Date – Week 09 (Sun, May 19, 2019 - 17:00) Assignment Details Background Business analytics and Data Mining techniques can help organizations make sense of -- and gain a competitive advantage from -- all the data that they have in their systems. Business analytics includes “decision management, content analytics, planning and forecasting, discovery and exploration, business intelligence, predictive analytics, data and content management, stream computing, data warehousing, information integration and governance” (IBM, 2013, p. 4). There are different types of business intelligence analytics that an organization can take advantage of, including predictive analytics, text analytics and text mining, sentiment analysis, customer analytics and business intelligence data mining. Data Mining is the process of analyzing large data-sets to identify trends and patterns in the data. The data can be generated through different sources such as social media, websites, transactions, mobile devices, sensors, etc. The information extracted from this data helps organizations to derive their real business value and generate new business opportunities. In the light of above information write a 3000 words research report on specific business analytics and Data Mining techniques applications that derive business value and generate new business opportunities in any of the following three (3) industry verticals. Illustrate the impact of these techniques on businesses with examples of application from the chosen domain. 1 Choose only any THREE (3) domains from the following list: 1. Transportation industry – in this domain the business analytics help stakeholders in making effective decision in Traffic control, route planning, intelligent transport systems and congestion management (by predicting traffic conditions). Also, could be useful for route planning to save on fuel and time, for travel arrangements in tourism etc. revenue management, technological enhancements, logistics and for competitive advantage (by consolidating shipments and optimizing freight movement), etc. 2. Banking industry - Data mining techniques can be used to detect financial fraud, including credit card fraud, corporate fraud and money laundering. 3. Health Care industry - Health care applications include discovery of patterns in radiological images, analysis of microarray (gene-chip) experimental data to cluster genes. Moreover, chronic disease states and high-risk patients can be tracked. 4. Manufacturing industry - Large volumes of data from the manufacturing industry are untapped. The underutilization of this information prevents improved quality of products, energy efficiency, reliability, and better profit margins. Business analytics can be used in solving today’s manufacturing challenges and to gain competitive advantage among other benefits. 5. Education industry - Major challenge in the education industry is to incorporate big data from different sources and vendors and to utilize it. Business analytics can be used to measure teacher’s effectiveness, overall progress of a student over time and effectiveness of curriculum, etc. 6. Customer Relationship Management - Data mining and analytics provides efficient tools to analyze customer data for the purpose of decision-making. Moreover, data mining aids analysis of buying patterns, determination of marketing strategies, segmentation of customers, stores or products. Requirements In this assignment, you will be required to form teams of approximately three (3) people. The findings of your research study will be presented through: • A group research report • Interactive presentation. 2 The report The report will take the form of a well-researched academic report of approximately 3000 words. Diagrams or tables are encouraged to be used to support your statements. The report should be well supported with appropriate references from reliable sources. You should include academic journals, books, theses, trade magazines and well-respected sources of related Internet materials that you find relevant. Please note – Wikipedia is NOT considered a reliable source to quote in an academic document of this type, without backup from other well reputed sources. Your report should present as a collective effort, not a series of submissions by various team members. It is expected to FLOW as one document. Each team member’s contribution should be clearly identified in the report, with a notation about which section he/she wrote about. Table of contents, reference list and contribution statements do not count towards the final words count. All reports must use the APA referencing style The Presentation Duration: 20 minutes for each team For the presentation component of this assessment, your team will focus on the following: 1. Business analytics and Data Mining techniques specific to the chosen domains 2. Illustration of applications of the above business analytics and Data Mining techniques within the chosen domains 3. Explanation on how these specific business analytics and Data Mining techniques added business value and generated new business opportunities within the chosen domains 4. Any Challenges that associated with the application of the above business analytics and Data Mining techniques for the chosen domains 3 Submission Submit your report as either a word or PDF document via Moodle. Marking Criteria/Rubric Refer to the attached marking guide. Feedback Feedback will be supplied through Moodle. Authoritative marks will be published through FdlGrades. Plagiarism: Plagiarism is the presentation of the expressed thought or work of another person as though it is one's own without properly acknowledging that person. You must not allow other students to copy your work and must take care to safeguard against this happening. More information about the plagiarism policy and procedure for the university can be found at http://federation.edu.au/students/learning-andstudy/online-help-with/plagiarism. 4 ITECH7406- Business Intelligence and Data Warehousing Research Report Marking Guide Sem3-2018 Criteria Marks Significance of Business analytics and applications for the chosen industry areas Data Mining /5 Research findings on Business analytics and Data Mining techniques specific to the chosen domains /10 Discussion on how business analytics and Data Mining techniques added business value and generated new business opportunities within the chosen domains /15 Report challenges that associated with the application of the business analytics and Data Mining techniques in the chosen domains /5 Introduction and Conclusion - An interesting, well written summary of the main points. For conclusion, an excellent final comment on the subject, based on the information provided. /5 References - Correct referencing (APA). All quoted material in quotes and acknowledged. All paraphrased material acknowledged. Correctly set out reference list. /5 Report Presentation Style – Spelling &grammar, length, originality, report layout , (Points will be deducted for exceedingly long or short reports. /5 General Comments: 5 Total /50 Marks /15 ITECH7406- Business Intelligence and Data Warehousing Research Presentation Marking Guide Sem3-2018 Criteria Marks Introduction - chosen industries and significance of analytics for the them /10 Industry specific Business analytics and Data Mining techniques /10 Applications of the business analytics and Data Mining techniques that added business value and generated new business opportunities within the chosen domains /15 Challenges that associated with the application of the above business analytics and Data Mining techniques for the chosen domains /5 Conclusion - an excellent final comment on the subject based on the research findings. /5 Presentation Style e.g. layout, clarity, engagement /5 General Comments: 6 Total /50 Marks /10
Purchase answer to see full attachment
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached.

Running head: REPORT RESEARCH

1

Report Research; Impact of Business Analytic and Data Mining Techniques on Education
Industries and Customer Relationship Management
Student’s Name
Institutional Affiliation
Instructor
Date

REPORT RESEARCH

2

Table of Contents
Abstract ........................................................................................................................................................ 1
1.Introduction............................................................................................................................................... 1
1.1 Education Industries Noe .................................................................................................................. 2
1.1.1 Education effectiveness ............................................................................................................... 3
1.1.2 Knowledge and Experience .......................................................................................................... 3
1.1.3 Education discoveries .................................................................................................................. 3
1.2 Customer Relationship Management ................................................................................................ 2
1.2.1 Application business pattern ....................................................................................................... 3
1.2.2 Segmentation of customer product............................................................................................. 3
1.1.2 Knowledge and Experience .......................................................................................................... 3
2. Conclusion ................................................................................................................................................ 1
References .................................................................................................................................................... 1

REPORT RESEARCH

3

Abstract
In an organization, data mining techniques and business analytics play an essential role in enabling
the business to acquire a competitive advantage over the other firms in the industry. Therefore, the
primary aim of this report is to illustrate the effect of data mining techniques and business analytics
on the education industry and customer relationship management. Based on the research that was
done by Symbiosis international university in 2016, indicate that business analytics and data mining
techniques enhance effectiveness within the education industry. In 2014, Dawson, a graduate at the
University of Wollongong carried out a research that portrayed on how the adoption of business
analytics and data mining techniques can install a lot of knowledge and experiences to the learning
students. Due to the challenge of incorporating big data from vendors and sources, learning analytics
(LA) have been applied in higher education to facilitate for more discoveries in education. This
review claims that business intelligence and analytics (BI&A) and other ground for big data analytics
have turned to be a most necessary form of building customer relationship management since they
can promote decision making in the organization through conduction data analysis that produce
business trend. Due to the challenge of incorporating big data from vendors and sources, learning
analytics (LA) have been applied in higher education to facilitate more discoveries in education.
Conclusively, business analytics, and data mining techniques are very crucial in education industries
and customers’ relationship management.

REPORT RESEARCH

4

1.Introduction
In an organization, data mining techniques and business analytics play an essential role in
enabling the business to acquire a competitive advantage over the oth...


Anonymous
I use Studypool every time I need help studying, and it never disappoints.

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Related Tags